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Statistics for the Behavioral Sciences [Hardback]

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  • Formāts: Hardback, 736 pages, height x width: 254x203 mm, Illustrations
  • Izdošanas datums: 07-Sep-2011
  • Izdevniecība: SAGE Publications Inc
  • ISBN-10: 141296931X
  • ISBN-13: 9781412969314
Citas grāmatas par šo tēmu:
Statistics for the Behavioral SciencesPalielināt
  • Formāts: Hardback, 736 pages, height x width: 254x203 mm, Illustrations
  • Izdošanas datums: 07-Sep-2011
  • Izdevniecība: SAGE Publications Inc
  • ISBN-10: 141296931X
  • ISBN-13: 9781412969314
Citas grāmatas par šo tēmu:
Permanent link: https://www.kriso.lv/db/9781412969314.html
Keywords:
An engaging introduction to statistics, the text provides readers with a tool for learning about behaviour without requiring a strong background in research methods. This comprehensive, yet conversational, text includes making sense sections to help relate and explain material that is often difficult for students to comprehend. The book provides instructions for using SPSS statistical software in each chapter with helpful examples and over 100 screen shots. Gregory Privitera takes a user-friendly approach while balancing statistical theory, computation, and application with the technical instruction needed for students to succeed in the modern era of data collection, analysis, and statistical interpretation. Key Features - 'making sense' sections break down the most difficult concepts in statistics for students, review important material, and basically "make sense" of the most challenging material. These sections are aimed at easing student stress, and making statistics more approachable. - 'research in focus' sections in Chapters 1 through 7 provide context by reviewing pertinent, current research that makes sense of or illustrates important statistical concepts discussed in the chapter. This feature prepares students to read research articles by providing examples on how a particular statistical method is reported. -"SPSS in focus" sections provide step-by-step, classroom-tested instruction using practical research examples for how the concepts taught in each chapter can be applied using SPSS. Students are supported with screen shot figures and explanations for how to read SPSS output. - numerous opportunities for practice are found in the 32-38 problems at the ends of each chapter. These are divided into different kinds of problems (factual problems, concept and application problems, and problems in research) categorized for easier identification and flexibility of assessment by instructors.
About the Author xxiv
Acknowledgments xxv
Preface to the Instructor xxvii
To the Student---How to Use SPSS With This Book xxxiv
PART I INTRODUCTION AND DESCRIPTIVE STATISTICS
xl
1 Introduction to Statistics
1(26)
1.1 Descriptive and Inferential Statistics
2(4)
Descriptive Statistics
2(2)
Inferential Statistics
4(1)
Making Sense---Populations and Samples
5(1)
1.2 Statistics in Research
6(6)
Experimental Method
7(2)
Quasi-Experimental Method
9(1)
Correlational Method
10(2)
1.3 Scales of Measurement
12(5)
Nominal Scales
12(1)
Ordinal Scales
13(2)
Interval Scales
15(1)
Ratio Scales
16(1)
1.4 Types of Data
17(2)
Continuous and Discrete Variables
17(1)
Quantitative and Qualitative Variables
17(2)
1.5 Research in Focus: Types of Data and Scales of Measurement
19(1)
1.6 SPSS in Focus: Entering and Defining Variables
20(7)
Chapter Summary Organized by Learning Objectives
23(1)
Key Terms
24(1)
End-of-Chapter Problems
24(1)
Factual Problems
24(1)
Concepts and Application Problems
24(2)
Problems in Research
26(1)
2 Summarizing Data: Tables, Graphs, and Distributions
27(40)
2.1 Why Summarize Data?
28(1)
2.2 Frequency Distributions for Grouped Data
29(11)
Simple Frequency Distributions
29(5)
Cumulative Frequency
34(2)
Relative Frequency
36(1)
Relative Percent
37(1)
Cumulative Relative Frequency and Cumulative Percent
38(2)
2.3 SPSS in Focus: Frequency Distributions for Quantitative Data
40(3)
2.4 Frequency Distributions for Ungrouped Data
43(1)
2.5 Research in Focus: Summarizing Demographic Information
44(1)
2.6 SPSS in Focus: Frequency Distributions for Categorical Data
45(1)
2.7 Pictorial Frequency Distributions
46(1)
2.8 Graphing Distributions: Continuous Data
47(6)
Histograms
48(1)
Frequency Polygons
49(1)
Ogives
49(2)
Stem-and-Leaf Displays
51(2)
2.9 Graphing Distributions: Discrete and Categorical Data
53(5)
Bar Charts
53(1)
Pie Charts
54(1)
Scatter Grams
55(3)
2.10 Research in Focus: Frequencies and Percents
58(1)
2.11 SPSS in Focus: Histograms, Bar Charts, and Pie Charts
58(9)
Chapter Summary Organized by Learning Objectives
60(1)
Key Terms
61(1)
End-of-Chapter Problems
62(1)
Factual Problems
62(1)
Concepts and Application Problems
62(3)
Problems in Research
65(2)
3 Summarizing Data: Central Tendency
67(28)
3.1 Introduction to Central Tendency
68(1)
3.2 Measures of Central Tendency
69(8)
The Mean
69(2)
The Weighted Mean
71(1)
Making Sense---Making the Grade
72(1)
The Median
73(3)
The Mode
76(1)
3.3 Characteristics of the Mean
77(5)
Changing an Existing Score
77(1)
Adding a New Score or Removing an Existing Score
78(1)
Adding, Subtracting, Multiplying, or Dividing Each Score by a Constant
79(1)
Summing the Differences of Scores From Their Mean
80(1)
Summing the Squared Differences of Scores From Their Mean
81(1)
3.4 Choosing an Appropriate Measure of Central Tendency
82(5)
Using the Mean to Describe Data
82(1)
Using the Median to Describe Data
83(2)
Using the Mode to Describe Data
85(2)
3.5 Research in Focus: Describing Central Tendency
87(1)
3.6 SPSS in Focus: Mean, Median, and Mode
88(7)
Chapter Summary Organized by Learning Objectives
90(1)
Key Terms
91(1)
End-of-Chapter Problems
91(1)
Factual Problems
91(1)
Concepts and Application Problems
91(2)
Problems in Research
93(2)
4 Summarizing Data: Variability
95(31)
4.1 Measuring Variability
96(1)
4.2 The Range
96(1)
4.3 Research in Focus: Reporting the Range
97(1)
4.4 Quartiles and Interquartiles
98(2)
4.5 The Variance
100(4)
Population Variance
101(2)
Sample Variance
103(1)
4.6 Explaining Variance for Populations and Samples
104(4)
The Numerator: Why Square Deviations From the Mean?
104(1)
The Denominator: Sample Variance as an Unbiased Estimator
105(2)
The Denominator: Degrees of Freedom
107(1)
4.7 The Computational Formula for Variance
108(4)
4.8 The Standard Deviation
112(3)
4.9 What Does the Standard Deviation Tell Us?
115(2)
Making Sense---Standard Deviation and Nonnormal Distributions
116(1)
4.10 Characteristics of the Standard Deviation
117(2)
4.11 SPSS in Focus: Range, Variance, and Standard Deviation
119(7)
Chapter Summary Organized by Learning Objectives
121(1)
Key Terms
122(1)
End-of-Chapter Problems
122(1)
Factual Problems
122(1)
Concepts and Application Problems
122(2)
Problems in Research
124(2)
PART II PROBABILITY AND THE FOUNDATIONS OF INFERENTIAL STATISTICS
126(98)
5 Probability
127(34)
5.1 Introduction to Probability
128(1)
5.2 Calculating Probability
128(3)
5.3 Probability and Relative Frequency
131(2)
5.4 The Relationship Between Multiple Outcomes
133(6)
Mutually Exclusive Outcomes
134(1)
Independent Outcomes
135(1)
Complementary Outcomes
136(1)
Conditional Outcomes
137(2)
5.5 Conditional Probabilities and Bayes' Theorem
139(2)
5.6 SPSS in Focus: Probability Tables
141(2)
Construct a Probability Table
141(1)
Construct a Conditional Probability Table
142(1)
5.7 Probability Distributions
143(2)
5.8 The Mean of a Probability Distribution and Expected Value
145(3)
Making Sense---Expected Values and the "Long-Term Mean"
147(1)
5.9 Research in Focus: When Are Risks Worth Taking?
148(1)
5.10 The Variance and Standard Deviation of a Probability Distribution
149(3)
5.11 Expected Value and the Binomial Distribution
152(3)
The Mean of a Binomial Distribution
153(1)
The Variance and Standard Deviation of a Binomial Distribution
153(2)
5.12 A Final Thought on the Likelihood of Random Behavioral Outcomes
155(6)
Chapter Summary Organized by Learning Objectives
156(1)
Key Terms
157(1)
End-of-Chapter Problems
157(1)
Factual Problems
157(1)
Concepts and Application Problems
158(1)
Problems in Research
159(2)
6 Probability and Normal Distributions
161(32)
6.1 The Normal Distribution in Behavioral Science
162(1)
6.2 Characteristics of the Normal Distribution
162(2)
6.3 Research in Focus: The Statistical Norm
164(2)
6.4 The Standard Normal Distribution
166(2)
6.5 The Unit Normal Table: A Brief Introduction
168(2)
6.6 Locating Proportions
170(6)
Locating Proportions Above the Mean
170(2)
Locating Proportions Below the Mean
172(2)
Locating Proportions Between Two Values
174(2)
6.7 Locating Scores
176(3)
6.8 SPSS in Focus: Converting Raw Scores to Standard z-Scores
179(3)
Making Sense---Standard Deviation and the Normal Distribution
180(2)
6.9 Going From Binomial to Normal
182(3)
6.10 The Normal Approximation to the Binomial Distribution
185(8)
Chapter Summary Organized by Learning Objectives
188(1)
Key Terms
189(1)
End-of-Chapter Problems
189(1)
Factual Problems
189(1)
Concepts and Application Problems
189(2)
Problems in Research
191(2)
7 Probability and Sampling Distributions
193(31)
7.1 Selecting Samples From Populations
194(3)
Inferential Statistics and Sampling Distributions
194(1)
Sampling and Conditional Probabilities
195(2)
7.2 Selecting a Sample: Who's in and Who's out?
197(4)
Sampling Strategy: The Basis for Statistical Theory
198(1)
Sampling Strategy: Most Used in Behavioral Research
199(2)
7.3 Sampling Distributions: The Mean
201(4)
Unbiased Estimator
202(1)
Central Limit Theorem
202(2)
Minimum Variance
204(1)
Overview of the Sample Mean
204(1)
7.4 Sampling Distributions: The Variance
205(4)
Unbiased Estimator
206(1)
Skewed Distribution Rule
207(1)
No Minimum Variance
207(1)
Making Sense---Minimum Variance Versus Unbiased Estimator
208(1)
Overview of the Sample Variance
209(1)
7.5 The Standard Error of the Mean
209(2)
7.6 Factors that Decrease Standard Error
211(1)
7.7 SPSS in Focus: Estimating the Standard Error of the Mean
212(2)
7.8 APA in Focus: Reporting the Standard Error
214(2)
7.9 Standard Normal Transformations With Sampling Distributions
216(8)
Chapter Summary Organized by Learning Objectives
220(1)
Key Terms
221(1)
End-of-Chapter Problems
221(1)
Factual Problems
221(1)
Concepts and Application Problems
222(1)
Problems in Research
223(1)
PART III PROBABILITY AND THE FOUNDATIONS OF INFERENTIAL STATISTICS
224(122)
8 Introduction to Hypothesis Testing
225(36)
8.1 Inferential Statistics and Hypothesis Testing
226(2)
8.2 Four Steps to Hypothesis Testing
228(4)
Making Sense---Testing the Null Hypothesis
229(3)
8.3 Hypothesis Testing and Sampling Distributions
232(2)
8.4 Making a Decision: Types of Error
234(2)
Decision: Retain the Null
234(1)
Decision: Retain the Null
235(1)
8.5 Testing a Research Hypothesis: Examples Using the z-Test
236(8)
Nondirectional, Two-Tailed, Hypothesis Tests
236(4)
Directional, Upper-Tail Critical, Hypothesis Tests
240(2)
Directional, Lower-Tail Critical, Hypothesis Tests
242(2)
8.6 Research in Focus: Directional Versus Nondirectional Tests
244(1)
8.7 Measuring the Size of an Effect: Cohen's d
245(3)
8.8 Effect Size, Power, and Sample Size
248(4)
The Relationship Between Effect Size and Power
248(3)
The Relationship Between Sample Size and Power
251(1)
8.9 Additional Factors That Increase Power
252(2)
Increasing Power: Increase Effect Size, Sample Size, and Alpha
252(1)
Increase power: Decrease Beta, Standard Deviation (σ), and Standard Error
253(1)
8.10 SPSS in Focus: A Preview for
Chapters 9 to 18
254(1)
8.11 APA in Focus: Reporting the Test Statistic and Effect Size
254(7)
Chapter Summary Organized by Learning Objectives
256(1)
Key Terms
257(1)
End-of-Chapter Problems
257(1)
Factual Problems
257(1)
Concepts and Application Problems
258(1)
Problems in Research
259(2)
9 Testing Means: Independent Sample t-Tests
261(32)
9.1 Going From z to t
262(1)
9.2 The Degrees of Freedom
263(1)
9.3 Reading the t-Table
264(1)
9.4 One-Independent Sample t-Test
265(4)
9.5 Effect Size for the One---Independent Sample t Test
269(3)
Estimated Cohen's d
269(1)
Proportion of Variance
270(2)
9.6 SPSS in Focus: One-Independent Sample t-Test
272(1)
9.7 Two-Independent Sample t-Test
273(8)
Making Sense---The Pooled Sample Variance
278(3)
9.8 Effect Size for the Two---Independent Sample t-Test
281(2)
Estimated Cohen's d
281(1)
Proportion of Variance
282(1)
9.9 SPSS in Focus: Two---Independent Sample t-Test
283(2)
9.10 APA in Focus: Reporting the t-Statistic and Effect Size
285(8)
Chapter Summary Organized by Learning Objectives
287(1)
Key Terms
288(1)
End-of-Chapter Problems
289(1)
Factual Problems
289(1)
Concepts and Application Problems
289(2)
Problems in Research
291(2)
10 Testing Means: Related Samples t-Test
293(26)
10.1 Related and Independent Samples
294(3)
Repeated-Measures Design
294(1)
Matched-Pairs Design
295(2)
10.2 Introduction to the Related Samples t-Test
297(3)
The Test Statistic
299(1)
Degrees of Freedom
300(1)
Assumptions
300(1)
10.3 Related Samples t-Test: Repeated-Measures Design
300(5)
Making Sense---Increasing Power by Reducing Error
304(1)
10.4 SPSS in Focus: The Related Samples t-Test
305(2)
10.5 Related Samples t-Test: Matched-Pairs Design
307(3)
10.6 Measuring Effect Size for the Related Samples t-Test
310(2)
Estimated Cohen's d
310(1)
Proportion of Variance
311(1)
10.7 Advantages for Selecting Related Samples
312(1)
10.8 APA in Focus: Reporting the t-Statistic and Effect Size for Related Samples
312(7)
Chapter Summary Organized by Learning Objectives
313(1)
Key Terms
314(1)
End-of-Chapter Problems
314(1)
Factual Problems
314(1)
Concepts and Application Problems
314(3)
Problems in Research
317(2)
11 Estimation and Confidence Intervals
319(27)
11.1 Point Estimation and Interval Estimation
320(2)
11.2 The Process of Estimation
322(2)
11.3 Estimation for the One-Independent Sample z-Test
324(5)
Making Sense---Estimation, Significance, and Effect Size
328(1)
11.4 Estimation for the One---Independent Sample t-Test
329(3)
11.5 SPSS in Focus: Confidence Intervals for the One---Independent Sample t-Test
332(1)
11.6 Estimation for the Two---Independent Sample t-Test
333(2)
11.7 SPSS in Focus: Confidence Intervals for the Two---Independent Sample t-Test
335(1)
11.8 Estimation for the Related Samples t-Test
336(2)
11.9 SPSS in Focus: Confidence Intervals for the Related Samples t-Test
338(1)
11.10 Characteristics of Estimation: Precisions and Certainty
339(1)
11.11 APA in Focus: Reporting Confidence Intervals
340(6)
Chapter Summary Organized by Learning Objectives
341(1)
Key Terms
342(1)
End-of-Chapter Problems
342(1)
Factual Problems
342(1)
Concepts and Application Problems
342(3)
Problems in Research
345(1)
PART IV MAKING INFERENCES ABOUT THE VARIABILITY OF TWO OR MORE MEANS
346(124)
12 Analysis of Variance: One-Way Between-Subjects Design
347(40)
12.1 Increasing k: A Shift to Analyzing Variance
348(1)
12.2 An Introduction to Analysis of Variance
349(3)
Identifying the Type of ANOVA
349(1)
Two Ways to Select Independent Samples
350(1)
Changes in Notation
351(1)
12.3 Sources of Variation and the Test Statistic
352(3)
12.4 Degrees of Freedom
355(3)
12.5 The One-Way Between-Subjects ANOVA
358(8)
Making Sense---Mean Squares and Variance
365(1)
12.6 What Is the Next Step?
366(1)
12.7 Post Hoc Comparisons
367(5)
Fisher's Least Significant Difference (LSD) Test
369(1)
Tukey's Honestly Significant Difference (HSD) Test
370(2)
12.8 SPSS in Focus: The One-Way Between-Subjects ANOVA
372(5)
12.9 Measuring Effect Size
377(2)
Eta-Squared (η2 or R2)
377(1)
Omega-Squared (ω2)
377(2)
12.10 APA in Focus: Reporting the F Statistic, Significance, and Effect Size
379(8)
Chapter Summary Organized by Learning Objectives
380(1)
Key Terms
381(1)
End-of-Chapter Problems
382(1)
Factual Problems
382(1)
Concepts and Application Problems
382(3)
Problems in Research
385(2)
13 Analysis of Variance: One-Way Within-Subjects Design
387(38)
13.1 Observing the Same Participants Across Groups
388(1)
The One-Way Within-Subjects ANOVA
388(1)
Selecting Related Samples: The Within-Subjects Design
388(1)
13.2 Sources of Variation and the Test Statistic
388(5)
Between-Groups Variation
389(1)
Error Variation
389(3)
Making Sense---Sources of Error
392(1)
13.3 Degrees of Freedom
393(1)
13.4 The One-Way Within-Subjects ANOVA
393(10)
Making Sense---Mean Squares and Variance
403(1)
13.5 Post Hoc Comparison: Bonferroni Procedure
403(4)
13.6 SPSS in Focus: The One-Way Within-Subjects ANOVA
407(3)
13.7 Measuring Effect Size
410(2)
Partial Eta-Squared (η2p)
410(1)
Partial Omega-Squared (ω2p)
411(1)
13.8 The Within-Subjects Design: Consistency and Power
412(5)
13.9 APA in Focus: Reporting the F Statistic, Significance, and Effect Size
417(8)
Chapter Summary Organized by Learning Objectives
418(1)
Key Terms
419(1)
End-of-Chapter Problems
419(1)
Factual Problems
419(1)
Concepts and Application Problems
420(3)
Problems in Research
423(2)
14 Analysis of Variance: Two-Way Between-Subjects Factorial Design
425(45)
14.1 Observing Two Factors at the Same Time
426(1)
14.2 New Terminology and Notation
427(2)
14.3 Designs for the Two-Way ANOVA
429(3)
2-Between or Between-Subjects Design
429(1)
1-Between 1-Within or Mixed Design
430(1)
2-Within or Within-Subjects Design
431(1)
14.4 Describing Variability: Main Effects and Interactions
432(8)
Sources of Variability
432(2)
Testing Main Effects
434(2)
Testing the Interaction
436(2)
Making Sense---Graphing Interactions
438(1)
Outcomes and Order of Interpretation
439(1)
14.5 The Two-Way Between-Subjects ANOVA
440(10)
14.6 Analyzing Main Effects and Interactions
450(7)
Interactions: Simple Main Effect Tests
451(4)
Main Effects: Pairwise Comparisons
455(2)
14.7 Measuring Effect Size
457(1)
Eta-Squared (η2 or R2)
457(1)
Omega-Squared (ω2)
457(1)
14.8 SPSS in Focus: The Two-Way Between-Subjects ANOVA
458(2)
14.9 APA in Focus: Reporting Main Effects, Interactions, and Effect Size
460(10)
Chapter Summary Organized by Learning Objectives
462(1)
Key Terms
463(1)
End-of-Chapter Problems
464(1)
Factual Problems
464(1)
Concepts and Application Problems
464(3)
Problems in Research
467(3)
PART V MAKING INFERENCES ABOUT PATTERNS, FREQUENCIES, AND ORDINAL DATA
470(145)
15 Correlation
471(44)
15.1 Treating Factors as Dependent Measures
472(1)
15.2 Describing a Correlation
473(4)
The Direction of a Correlation
473(2)
The Strength of a Correlation
475(2)
15.3 Pearson Correlation Coefficient
477(6)
Making Sense---Understanding Covariance
479(2)
Effect Size: The Coefficient of Determination
481(1)
Hypothesis Testing: Testing for Significance
482(1)
15.4 SPSS in Focus: Pearson Correlation Coefficient
483(1)
15.5 Assumptions of Tests for Linear Correlations
484(3)
Homoscedasticity
485(1)
Linearity
485(1)
Normality
486(1)
15.6 Limitations in Interpretation: Causality, Outliers, and Restrictions of Range
487(4)
Causality
487(2)
Outliers
489(1)
Restriction of Range
489(2)
15.7 Alternative to Pearson r: Spearman Correlation Coefficient
491(3)
15.8 SPSS in Focus: Spearman Correlation Coefficient
494(2)
15.9 Alternative to Pearson r: Point-Biserial Correlation Coefficient
496(4)
15.10 SPSS in Focus: Point-Biserial Correlation Coefficient
500(1)
15.11 Alternative to Pearson r: Phi Correlation Coefficient
501(3)
15.12 SPSS in Focus: Phi Correlation Coefficient
504(2)
15.13 APA in Focus: Reporting Correlations
506(9)
Chapter Summary Organized by Learning Objectives
507(2)
Key Terms
509(1)
End-of-Chapter Problems
509(1)
Factual Problems
509(1)
Concepts and Application Problems
509(4)
Problems in Research
513(2)
16 Linear Regression
515(30)
16.1 From Relationships to Predictions
516(1)
16.2 Fundamentals of Linear Regression
516(2)
16.3 What Makes the Regression Line the Best-Fitting Line?
518(2)
16.4 The Slope and y Intercept of a Straight Line
520(2)
16.5 Using the Method of Least Squares to Find the Best Fit
522(4)
Making Sense---SP, SS, and the Slope of a Regression Line
524(2)
16.6 Using Analysis of Regression to Measure Significance
526(4)
16.7 SPSS in Focus: Analysis of Regression
530(2)
16.8 Using the Standard Error of Estimate to Measure Accuracy
532(3)
16.9 Multiple Regression
535(2)
16.10 APA in Focus: Reporting Regression Analysis
537(8)
Chapter Summary Organized by Learning Objectives
539(1)
Key Terms
540(1)
End-of-Chapter Problems
540(1)
Factual Problems
540(1)
Concepts and Application Problems
541(2)
Problems in Research
543(2)
17 Nonparametric Tests: Chi-Square Tests
545(32)
17.1 Tests for Nominal Data
546(1)
17.2 The Chi-Square Goodness-of-Fit Test
547(7)
The Test Statistic
549(1)
Making Sense---The Relative Size of a Discrepancy
549(1)
The Degrees of Freedom
550(1)
Making Sense---Degrees of Freedom
550(2)
Hypothesis Testing for Goodness of Fit
552(2)
17.3 SPSS in Focus: The Chi-Square Goodness-of-Fit Test
554(2)
17.4 Interpreting the Chi-Square Goodness-of-Fit Test
556(2)
Interpreting a Significant Chi-Square Goodness-of-Fit Test
556(1)
Using the Chi-Square Goodness-of-Fit Test to Support the Null Hypothesis
557(1)
17.5 Independent Observations and Expected Frequency Size
558(1)
17.6 The Chi-Square Test for Independence
559(6)
Determining Expected Frequencies
561(1)
The Test Statistic
562(1)
The Degrees of Freedom
562(1)
Hypothesis Testing for Independence
563(2)
17.7 The Relationship Between Chi-Square and the Phi Coefficient
565(1)
17.8 Measures of Effect Size
566(2)
Effect Size Using Proportion of Variance
567(1)
Effect Size Using the Phi Coefficient
567(1)
Effect Size Using Cramer's V
567(1)
17.9 SPSS in Focus: The Two-Way Chi-Square Test for Independence
568(2)
17.10 APA in Focus: Reporting the Chi-Square Test
570(7)
Chapter Summary Organized by Learning Objectives
571(1)
Key Terms
572(1)
End-of-Chapter Problems
572(1)
Factual Problems
572(1)
Concepts and Application Problems
573(2)
Problems in Research
575(2)
18 Nonparametric Tests: Tests for Ordinal Data
577(38)
18.1 Tests for Ordinal Data
578(2)
Scales of Measurement and Variance
578(1)
Making Sense---Reducing Variability
578(1)
Minimizing Bias: Tied Ranks
579(1)
18.2 The Sign Test
580(6)
One-Sample Sign Test
580(3)
Related Samples Sign Test
583(2)
The Normal Approximation for the Sign Test
585(1)
18.3 SPSS in Focus: The Related Samples Sign Test
586(2)
18.4 The Wilcoxon Signed-Ranks T Test
588(4)
Interpretation of the Test Statistic T
590(1)
The Normal Approximation for the Wilcoxon T
591(1)
18.5 SPSS in Focus: The Wilcoxon Signed-Ranks T Test
592(1)
18.6 The Mann-Whitney U Test
593(5)
Interpretation of the Test Statistic U
596(1)
Computing the Test Statistic U
596(1)
The Normal Approximation for U
597(1)
18.7 SPSS in Focus: The Mann-Whitney U Test
598(2)
18.8 The Kruskal-Wallis H Test
600(3)
Interpretation of the Test Statistic H
602(1)
18.9 SPSS in Focus: The Kruskal-Wallis H Test
603(1)
18.10 The Friedman Test
604(3)
Interpretation of the Test Statistic X2R
606(1)
18.11 SPSS in Focus: The Friedman Test
607(1)
18.12 APA in Focus: Reporting Nonparametric Tests
608(7)
Chapter Summary Organized by Learning Objectives
609(2)
Key Terms
611(1)
End-of-Chapter Problems
611(1)
Factual Problems
611(1)
Concepts and Application Problems
611(2)
Problems in Research
613(2)
Afterword
615(2)
Appendix A Mathematics in Statistics
617(12)
A.1 Positive and Negative Numbers
617(1)
A.2 Addition
618(1)
A.3 Subtraction
618(1)
A.4 Multiplication
619(1)
A.5 Division
619(1)
A.6 Fractions
620(2)
A.7 Decimals and Percents
622(1)
A.8 Exponents and Roots
623(1)
A.9 Order of Computation
624(1)
A.10 Equations: Solving for x
625(1)
A.11 Summation Notation
626(3)
Appendix B Statistical Tables
629(18)
Table B.1 The Unit Normal Table
629(4)
Table B.2 The t-Distribution
633(1)
Table B.3 Critical Values for F-Distribution
634(3)
Table B.4 The Studentized Range Statistic (q)
637(2)
Table B.5 Critical Values for the Pearson Correlation
639(2)
Table B.6 Critical Values for the Spearman Correlation
641(1)
Table B.7 Critical Values of Chi-Square (X2)
642(1)
Table B.8 Distribution of Binomial Probabilities
643(1)
Table B.9 Wilcoxon Signed-Rank T Critical Values
644(1)
Table B.10 Critical Values of the Mann-Whitney U
645(2)
Appendix C
Chapter Solutions for Even-Numbered Problems
647
Glossary 1(1)
References 1(1)
Index 1
Gregory J. Privitera is an Associate Professor of Psychology at St. Bonaventure University. He received his Ph.D. in Behavioral Neuroscience at the University at Buffalo and went on to complete post-doctoral research at Arizona State University before coming to St. Bonaventure. A veteran of the U.S. Marines, he is also the author of more than two dozen peer-reviewed articles and books on the role of social cognition and learning on eating behavior and health. His work has been recognized in a variety of ways, including university awards for teaching and research. He oversees a variety of undergraduate research projects at St. Bonaventure University with more than a dozen undergraduate student research projects leading to publication in peer-reviewed journals. In the community, Dr. Privitera is a member of the Board of Trustees for a local elementary and high school where his children attend the elementary school.